Displaying publications 1 - 20 of 24 in total

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  1. The past, present and future of imaging in multiple sclerosis
    Ramli N, Rahmat K, Azmi K, Chong HT
    J Clin Neurosci, 2010 Apr;17(4):422-7.
    PMID: 20167498 DOI: 10.1016/j.jocn.2009.09.014
    Despite technological advances in imaging, multiple sclerosis (MS) remains a clinical diagnosis that is supported, but not replaced, by laboratory or imaging findings. However, imaging is essential in the current diagnostic criteria of MS, for prediction of the likelihood of MS for patients with clinically isolated syndromes, correlation with lesion pathology and assessment of treatment outcome. This article gives an overview of imaging in MS with particular emphasis on the role of MRI in various diagnostic imaging criteria. Novel imaging for MS using 3 Tesla field strengths, magnetization transfer imaging, diffusion tensor imaging, magnetic resonance spectroscopy and cell-specific contrast will be reviewed.
    Matched MeSH terms: Diagnostic Imaging/methods*
  2. Advances and opportunities in nanoimaging agents for the diagnosis of inflammatory lung diseases
    Masanam HB, Perumal G, Krishnan S, Singh SK, Jha NK, Chellappan DK, et al.
    Nanomedicine (Lond), 2022 Oct;17(25):1981-2005.
    PMID: 36695290 DOI: 10.2217/nnm-2021-0427
    The development of rapid, noninvasive diagnostics to detect lung diseases is a great need after the COVID-2019 outbreak. The nanotechnology-based approach has improved imaging and facilitates the early diagnosis of inflammatory lung diseases. The multifunctional properties of nanoprobes enable better spatial-temporal resolution and a high signal-to-noise ratio in imaging. Targeted nanoimaging agents have been used to bind specific tissues in inflammatory lungs for early-stage diagnosis. However, nanobased imaging approaches for inflammatory lung diseases are still in their infancy. This review provides a solution-focused approach to exploring medical imaging technologies and nanoprobes for the detection of inflammatory lung diseases. Prospects for the development of contrast agents for lung disease detection are also discussed.
    Matched MeSH terms: Diagnostic Imaging/methods
  3. Fulltext Evaluation of digital clubbing
    Chan CW
    Aust Fam Physician, 2015 Mar;44(3):113-6.
    PMID: 25770575
    Matched MeSH terms: Diagnostic Imaging/methods*
  4. Autoinflammatory diseases in childhood, part 1: monogenic syndromes
    Navallas M, Inarejos Clemente EJ, Iglesias E, Rebollo-Polo M, Zaki FM, Navarro OM
    Pediatr Radiol, 2020 03;50(3):415-430.
    PMID: 32065272 DOI: 10.1007/s00247-019-04536-9
    Autoinflammatory diseases constitute a family of disorders defined by aberrant stimulation of inflammatory pathways without involving antigen-directed autoimmunity. They may be divided into monogenic and polygenic types. Monogenic autoinflammatory syndromes are those with identified genetic mutations, such as familial Mediterranean fever, tumor necrosis factor receptor-associated periodic fever syndrome (TRAPS), mevalonate kinase deficiency or hyperimmunoglobulin D syndrome, cryopyrin-associated periodic fever syndromes (CAPS), pyogenic arthritis pyoderma gangrenosum and acne (PAPA) syndrome, interleukin-10 and interleukin-10 receptor deficiencies, adenosine deaminase 2 deficiency and pediatric sarcoidosis. Those without an identified genetic mutation are known as polygenic and include systemic-onset juvenile idiopathic arthritis, idiopathic recurrent acute pericarditis, Behçet syndrome, chronic recurrent multifocal osteomyelitis and inflammatory bowel disease among others. Autoinflammatory disorders are defined by repeating episodes or persistent fever, rash, serositis, lymphadenopathy, arthritis and increased acute phase reactants, and thus may mimic infections clinically. Most monogenic autoinflammatory syndromes present in childhood. However, because of their infrequency, diverse and nonspecific presentation, and the relatively new genetic recognition, diagnosis is usually delayed. In this article, which is Part 1 of a two-part series, the authors update monogenic autoinflammatory diseases in children with special emphasis on imaging features that may help establish the correct diagnosis.
    Matched MeSH terms: Diagnostic Imaging/methods*
  5. Fulltext 3D printing in medical imaging and healthcare services
    Abdullah KA, Reed W
    J Med Radiat Sci, 2018 Sep;65(3):237-239.
    PMID: 29971971 DOI: 10.1002/jmrs.292
    Three-dimensional (3D) printing technology has demonstrated a huge potential for the future of medicine. Since its introduction, it has been used in various areas, for example building anatomical models, personalising medical devices and implants, aiding in precision medical interventions and the latest development, 3D bioprinting. This commentary is provided to outline the current use of 3D printing in medical imaging and its future directions for advancing the healthcare services.
    Matched MeSH terms: Diagnostic Imaging/methods*
  6. Image analysis procedure for the optical scanning of fine-root dynamics: errors depending on the observer and root-viewing window size
    Kume T, Ohashi M, Makita N, Kho LK, Katayama A, Endo I, et al.
    Tree Physiol, 2018 12 01;38(12):1927-1938.
    PMID: 30452737 DOI: 10.1093/treephys/tpy124
    Clarifying the dynamics of fine roots is critical to understanding carbon and nutrient cycling in forest ecosystems. An optical scanner can potentially be used in studying fine-root dynamics in forest ecosystems. The present study examined image analysis procedures suitable for an optical scanner having a large (210 mm × 297 mm) root-viewing window. We proposed a protocol for analyzing whole soil images obtained by an optical scanner that cover depths of 0-210 mm. We tested our protocol using six observers with different experience in studying roots. The observers obtained data from the manual digitization of sequential soil images recorded for a Bornean tropical forest according to the protocol. Additionally, the study examined the potential tradeoff between the soil image size and accuracy of estimates of fine-root dynamics in a simple exercise. The six observers learned the protocol and obtained similar temporal patterns of fine-root growth and biomass with error of 10-20% regardless of their experience. However, there were large errors in decomposition owing to the low visibility of decomposed fine roots. The simple exercise revealed that a smaller root-viewing window (smaller than 60% of the original window) produces patterns of fine-root dynamics that are different from those for the original window size. The study showed the high applicability of our image analysis approach for whole soil images taken by optical scanners in estimating the fine-root dynamics of forest ecosystems.
    Matched MeSH terms: Diagnostic Imaging/methods
  7. Fulltext Injury to ulnar collateral ligament of thumb
    Madan SS, Pai DR, Kaur A, Dixit R
    Orthop Surg, 2014 Feb;6(1):1-7.
    PMID: 24590986 DOI: 10.1111/os.12084
    Injury of the ulnar collateral ligament (UCL) of thumb can be incapacitating if untreated or not treated properly. This injury is notorious for frequently being missed by inexperienced health care personnel in emergency departments. It has frequently been described in skiers, but also occurs in other sports such as rugby, soccer, handball, basketball, volleyball and even after a handshake. The UCL of the thumb acts as a primary restraint to valgus stress and is injured if hyperabduction and hyperextension forces are applied to the first metacarpophalangeal joint. The diagnosis is best established clinically, though MRI is the imaging modality of choice. Many treatment options exist, surgical treatment being offered depending on various factors, including timing of presentation (acute or chronic), grade (severity of injury), displacement (Stener lesion), location of tear (mid-substance or peripheral), associated or concomitant surrounding tissue injury (bone, volar plate, etc.), and patient-related factors (occupational demands, etc.). This review aims to identify the optimal diagnostic techniques and management options for UCL injury available thus far.
    Matched MeSH terms: Diagnostic Imaging/methods
  8. Fulltext Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor
    Rahman HA, Harun SW, Arof H, Irawati N, Musirin I, Ibrahim F, et al.
    J Biomed Opt, 2014 May;19(5):057009.
    PMID: 24839996 DOI: 10.1117/1.JBO.19.5.057009
    An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.
    Matched MeSH terms: Diagnostic Imaging/methods
  9. Reflection coefficient detection of simulation models for microwave imaging simulation system
    Chew KM, Sudirman R, Seman N, Yong CY
    Biomed Mater Eng, 2014;24(1):199-207.
    PMID: 24211899 DOI: 10.3233/BME-130800
    The study was conducted based on two objectives as framework. The first objective is to determine the point of microwave signal reflection while penetrating into the simulation models and, the second objective is to analyze the reflection pattern when the signal penetrate into the layers with different relative permittivity, εr. Thus, several microwave models were developed to make a close proximity of the in vivo human brain. The study proposed two different layers on two different characteristics models. The radii on the second layer and the corresponding antenna positions are the factors for both models. The radii for model 1 is 60 mm with an antenna position of 10 mm away, in contrast, model 2 is 10 mm larger in size with a closely adapted antenna without any gap. The layers of the models were developed with different combination of materials such as Oil, Sandy Soil, Brain, Glycerin and Water. Results show the combination of Glycerin + Brain and Brain + Sandy Soil are the best proximity of the in vivo human brain grey and white matter. The results could benefit subsequent studies for further enhancement and development of the models.
    Matched MeSH terms: Diagnostic Imaging/methods*
  10. Diagnosis of diabetic retinopathy: automatic extraction of optic disc and exudates from retinal images using marker-controlled watershed transformation
    Reza AW, Eswaran C, Dimyati K
    J Med Syst, 2011 Dec;35(6):1491-501.
    PMID: 20703768 DOI: 10.1007/s10916-009-9426-y
    Due to increasing number of diabetic retinopathy cases, ophthalmologists are experiencing serious problem to automatically extract the features from the retinal images. Optic disc (OD), exudates, and cotton wool spots are the main features of fundus images which are used for diagnosing eye diseases, such as diabetic retinopathy and glaucoma. In this paper, a new algorithm for the extraction of these bright objects from fundus images based on marker-controlled watershed segmentation is presented. The proposed algorithm makes use of average filtering and contrast adjustment as preprocessing steps. The concept of the markers is used to modify the gradient before the watershed transformation is applied. The performance of the proposed algorithm is evaluated using the test images of STARE and DRIVE databases. It is shown that the proposed method can yield an average sensitivity value of about 95%, which is comparable to those obtained by the known methods.
    Matched MeSH terms: Diagnostic Imaging/methods
  11. Neonatal tumours in Malaysia: a call for heightened awareness
    Yeap BH, Zahari Z
    Pediatr Surg Int, 2010 Feb;26(2):207-12.
    PMID: 19943053 DOI: 10.1007/s00383-009-2523-7
    Neonatal neoplasms are rare tumours notorious for their atypical presentation and unpredictable behaviour. Their optimal treatment remains uncertain, a dilemma compounded by the deleterious effects of adjuvant chemo- or radiotherapy during this vulnerable period of growth. This paper examined the relatively high incidence of these tumours and its impact on paediatric surgery in Malaysia.
    Matched MeSH terms: Diagnostic Imaging/methods*
  12. Disseminated tuberculosis infection: a 'super' 18F-FDG PET/CT appearance
    Nordin AJ, Rossetti C, Rahim NA
    Eur. J. Nucl. Med. Mol. Imaging, 2009 May;36(5):882.
    PMID: 19296106 DOI: 10.1007/s00259-009-1107-z
    Matched MeSH terms: Diagnostic Imaging/methods
  13. Automatic multilevel medical image annotation and retrieval
    Mueen A, Zainuddin R, Baba MS
    J Digit Imaging, 2008 Sep;21(3):290-5.
    PMID: 17846834
    Image retrieval at the semantic level mostly depends on image annotation or image classification. Image annotation performance largely depends on three issues: (1) automatic image feature extraction; (2) a semantic image concept modeling; (3) algorithm for semantic image annotation. To address first issue, multilevel features are extracted to construct the feature vector, which represents the contents of the image. To address second issue, domain-dependent concept hierarchy is constructed for interpretation of image semantic concepts. To address third issue, automatic multilevel code generation is proposed for image classification and multilevel image annotation. We make use of the existing image annotation to address second and third issues. Our experiments on a specific domain of X-ray images have given encouraging results.
    Matched MeSH terms: Diagnostic Imaging/methods*
  14. Gold nanostars-diagnosis, bioimaging and biomedical applications
    Mousavi SM, Zarei M, Hashemi SA, Ramakrishna S, Chiang WH, Lai CW, et al.
    Drug Metab Rev, 2020 05;52(2):299-318.
    PMID: 32150480 DOI: 10.1080/03602532.2020.1734021
    Gold Nanostars (GNS) have attracted tremendous attention toward themselves owing to their multi-branched structure and unique properties. These state of the art metallic nanoparticles possess intrinsic features like remarkable optical properties and exceptional physiochemical activities. These star-shaped gold nanoparticles can predominantly be utilized in biosensing, photothermal therapy, imaging, surface-enhanced Raman spectroscopy and target drug delivery applications due to their low toxicity and extraordinary optical features. In the current review, recent approaches in the matter of GNS in case of diagnosis, bioimaging and biomedical applications were summarized and reported. In this regard, first an overview about the structure and general properties of GNS were reported and thence detailed information regarding the diagnostic, bioimaging, photothermal therapy, and drug delivery applications of such novel nanomaterials were presented in detail. Summarized information clearly highlighting the superior capability of GNS as potential multi-functional materials for biomedical applications.
    Matched MeSH terms: Diagnostic Imaging/methods
  15. Diseases diagnosis using fuzzy logic methods: A systematic and meta-analysis review
    Ahmadi H, Gholamzadeh M, Shahmoradi L, Nilashi M, Rashvand P
    Comput Methods Programs Biomed, 2018 Jul;161:145-172.
    PMID: 29852957 DOI: 10.1016/j.cmpb.2018.04.013
    BACKGROUND AND OBJECTIVE: Diagnosis as the initial step of medical practice, is one of the most important parts of complicated clinical decision making which is usually accompanied with the degree of ambiguity and uncertainty. Since uncertainty is the inseparable nature of medicine, fuzzy logic methods have been used as one of the best methods to decrease this ambiguity. Recently, several kinds of literature have been published related to fuzzy logic methods in a wide range of medical aspects in terms of diagnosis. However, in this context there are a few review articles that have been published which belong to almost ten years ago. Hence, we conducted a systematic review to determine the contribution of utilizing fuzzy logic methods in disease diagnosis in different medical practices.

    METHODS: Eight scientific databases are selected as an appropriate database and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed as the basis method for conducting this systematic and meta-analysis review. Regarding the main objective of this research, some inclusion and exclusion criteria were considered to limit our investigation. To achieve a structured meta-analysis, all eligible articles were classified based on authors, publication year, journals or conferences, applied fuzzy methods, main objectives of the research, problems and research gaps, tools utilized to model the fuzzy system, medical disciplines, sample sizes, the inputs and outputs of the system, findings, results and finally the impact of applied fuzzy methods to improve diagnosis. Then, we analyzed the results obtained from these classifications to indicate the effect of fuzzy methods in decreasing the complexity of diagnosis.

    RESULTS: Consequently, the result of this study approved the effectiveness of applying different fuzzy methods in diseases diagnosis process, presenting new insights for researchers about what kind of diseases which have been more focused. This will help to determine the diagnostic aspects of medical disciplines that are being neglected.

    CONCLUSIONS: Overall, this systematic review provides an appropriate platform for further research by identifying the research needs in the domain of disease diagnosis.

    Matched MeSH terms: Diagnostic Imaging/methods*
  16. Fulltext Corneo-pterygium total area measurements utilising image analysis method
    Mohd Radzi H, Khairidzan MK, Mohd Zulfaezal CA, Azrin EA
    J Optom, 2019 05 13;12(4):272-277.
    PMID: 31097348 DOI: 10.1016/j.optom.2019.04.001
    PURPOSE: To describe an objective method to accurately quantify corneo-pterygium total area (CPTA) by utilising image analysis method and to evaluate its association with corneal astigmatism (CA).

    METHODS: 120 primary pterygium participants were selected from patients who visited an ophthalmology clinic. We adopted image analysis software in calculating the size of invading pterygium to the cornea. The marking of the calculated area was done manually, and the total area size was measured in pixel. The computed area is defined as the area from the apex of pterygium to the limbal-corneal border. Then, from the pixel, it was transformed into a percentage (%), which represents the CPTA relative to the entire corneal surface area. Intra- and inter-observer reliability testing were performed by repeating the tracing process twice with a different sequence of images at least one (1) month apart. Intraclass correlation (ICC) and scatter plot were used to describe the reliability of measurement.

    RESULTS: The overall mean (N=120) of CPTA was 45.26±13.51% (CI: 42.38-48.36). Reliability for region of interest (ROI) demarcation of CPTA were excellent with intra and inter-agreement of 0.995 (95% CI, 0.994-0.998; P<0.001) and 0.994 (95% CI, 0.992-0.997; P<0.001) respectively. The new method was positively associated with corneal astigmatism (P<0.01). This method was able to predict 37% of the variance in CA compared to 21% using standard method.

    CONCLUSIONS: Image analysis method is useful, reliable and practical in the clinical setting to objectively quantify actual pterygium size, shapes and its effects on the anterior corneal curvature.

    Matched MeSH terms: Diagnostic Imaging/methods*
  17. MRI Imaging, Comparison of MRI with other Modalities, Noise in MRI Images and Machine Learning Techniques for Noise Removal: A Review
    Khan SU, Ullah N, Ahmed I, Ahmad I, Mahsud MI
    Curr Med Imaging Rev, 2019;15(3):243-254.
    PMID: 31989876 DOI: 10.2174/1573405614666180726124952
    BACKGROUND: Medical imaging is to assume greater and greater significance in an efficient and precise diagnosis process.

    DISCUSSION: It is a set of various methodologies which are used to capture internal or external images of the human body and organs for clinical and diagnosis needs to examine human form for various kind of ailments. Computationally intelligent machine learning techniques and their application in medical imaging can play a significant role in expediting the diagnosis process and making it more precise.

    CONCLUSION: This review presents an up-to-date coverage about research topics which include recent literature in the areas of MRI imaging, comparison with other modalities, noise in MRI and machine learning techniques to remove the noise.

    Matched MeSH terms: Diagnostic Imaging/methods*
  18. Fulltext A new blood vessel extraction technique using edge enhancement and object classification
    Badsha S, Reza AW, Tan KG, Dimyati K
    J Digit Imaging, 2013 Dec;26(6):1107-15.
    PMID: 23515843 DOI: 10.1007/s10278-013-9585-8
    Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic method to extract the retinal blood vessel. The proposed method comprises several basic image processing techniques, namely edge enhancement by standard template, noise removal, thresholding, morphological operation, and object classification. The proposed method has been tested on a set of retinal images. The retinal images were collected from the DRIVE database and we have employed robust performance analysis to evaluate the accuracy. The results obtained from this study reveal that the proposed method offers an average accuracy of about 97 %, sensitivity of 99 %, specificity of 86 %, and predictive value of 98 %, which is superior to various well-known techniques.
    Matched MeSH terms: Diagnostic Imaging/methods
  19. Automatic tracing of optic disc and exudates from color fundus images using fixed and variable thresholds
    Reza AW, Eswaran C, Hati S
    J Med Syst, 2009 Feb;33(1):73-80.
    PMID: 19238899
    The detection of bright objects such as optic disc (OD) and exudates in color fundus images is an important step in the diagnosis of eye diseases such as diabetic retinopathy and glaucoma. In this paper, a novel approach to automatically segment the OD and exudates is proposed. The proposed algorithm makes use of the green component of the image and preprocessing steps such as average filtering, contrast adjustment, and thresholding. The other processing techniques used are morphological opening, extended maxima operator, minima imposition, and watershed transformation. The proposed algorithm is evaluated using the test images of STARE and DRIVE databases with fixed and variable thresholds. The images drawn by human expert are taken as the reference images. The proposed method yields sensitivity values as high as 96.7%, which are better than the results reported in the literature.
    Matched MeSH terms: Diagnostic Imaging/methods*
  20. Fulltext Computed tomography of blunt renal trauma
    Razali MR, Azian AA, Amran AR, Azlin S
    Singapore Med J, 2010 Jun;51(6):468-73; quiz 474.
    PMID: 20658105
    Renal injury is observed in 10 percent of cases of abdominal trauma, and the majority (80 percent to 90 percent) of these are attributable to blunt trauma. Intravenous urography and ultrasonography of the abdomen were previously the modalities of choice in the imaging of renal injuries. However, computed tomography (CT) is currently the imaging modality of choice in the evaluation of blunt renal injury, since it provides the exact staging of renal injuries. The purpose of this article is to describe the CT staging of renal injuries observed in blunt abdominal trauma based on the Federle Classification and the American Association for the Surgery of Trauma renal injury severity scale.
    Matched MeSH terms: Diagnostic Imaging/methods
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